INTRODUCTION

Historically, in developing countries, coastal communities have obtained food and income from artisanal fishing (Ding et al., 2017; Chande et al., 2019). This activity is carried out by the poorest and most vulnerable fishing communities and contributes to the economic and social sustainability of the regions (Mendelsohn et al., 2006; Ferro et al., 2019). In the southern Pacific of Colombia, there are impacts and threats for artisanal fishermen, including the negative effects of climate change (i.e., flooding, increased storm intensity and frequency, and changes in the distribution, composition, and abundance of fish species), non-climatic stressors (i.e., the reduction and anthropogenic destruction of habitats, overfishing, and marine pollution), and socioeconomic and political factors such as poor living conditions, state abandonment, low financial support, and social conflicts (Lancker et al., 2019; Sumaila, 2019; Talloni et al., 2019; Jara et al., 2020; Macusi et al., 2020; Mendenhall et al., 2020). This negatively impacts the population’s food security and income, as its effects are manifested in increased fuel costs and fishing efforts, the use of unregulated fishing gear such as runches and changas, displacement to areas where fishing was not previously practiced (e.g., river mouths), catching sizes not previously considered for sale or consumption, and a decrease in landings (Lancker et al., 2019; Sumaila, 2019; Talloni et al., 2019; Jara et al., 2020; Macusi et al., 2020; Mendenhall et al., 2020). In addition to these impacts and threats that make fishermen vulnerable, there is also little state support for implementing measures aimed at minimizing the risks associated with this activity (Díaz et al., 2011; González et al., 2015; Arroyo et al., 2016; Departamento Administrativo Nacional de Estadística, 2018; Herrera et al., 2019). On the other hand, reducing the vulnerability of artisanal fishermen’s households depends on adaptation strategies such as occupational mobility, some elements of social capital, and reduced dependence on the resource, which could constitute an input for the creation of a public policy that guides efforts towards strategies for the sustainability of the households of fishermen who continue to choose fishing as their main economic activity, as well as for the generation of other means of livelihood (Selvaraj et al., 2022a).

Various authors suggest that strategies should be implemented which allow reducing the high level of poverty, increasing state support, promoting associativity, reducing the population’s exposure to climatic threats, ensuring the sustainable use of ecosystems that provide environmental goods and services, and increasing access to public services, thereby improving their adaptation capacity and overall well-being (Saavedra-Díaz et al., 2015; Arroyo et al., 2016; Jiménez and Saavedra, 2019). Among the measures expected to reduce the vulnerability of fishermen are the creation of marine reserves, changes in fishing practices, the training and education of fishermen regarding possible climatic consequences, the creation of associations and support networks, and government support, such as subsidies and incentives for good fishing practices (López et al., 2008; Rosas et al., 2014).

Marine Protected Areas (MPAs) are an example of natural resource management and mitigation and adaptation to climate change, as they contain representative samples of ecologically important ecosystems, make the surrounding territories more adaptable, and strengthen society to face the impacts generated by overfishing (Le Cornu et al., 2018; Baker et al., 2019). This strategy is mainly based on the fact that these areas maintain essential ecosystem services that benefit people both directly and indirectly, among which are climate regulation and resource provisioning (Herrera Carmona et al., 2014). The management of natural resources as an adaptation strategy has been evaluated, finding that MPAs increase coastal species population and oceanic production, which enhances the former’s ability to adapt to the negative effects of climate change (Dey et al., 2016a, 2016b; Rosegrant et al., 2016).

Ecosystem-based adaptation (EbA) reduces the vulnerability of people and ecosystems to the effects of climate change and other threats through conservation and sustainable use actions, ensuring that ecosystems continue to provide essential goods and services to communities despite projected impacts (Álvarez et al., 2018). As an EbA strategy, MPAs with a focus on sustainable use arise as a tool that guarantees the protection of habitats, biodiversity, and ecosystem services, so that the fishery resource is maintained and its associated activities are sustainable (le Pape et al., 2014; Timonet and Abecasis, 2020). Some studies indicate that, in mangrove coasts, EbA is beneficial in adapting to climate change regardless of the climatic stressors faced by the system and the population that benefits from it (Sierra and Cantera, 2015).

In the northern Colombian Pacific, there is an Exclusive Zone for Artisanal Fishing (EZAF) where capture is regulated (due to overexploitation and industrial fishing), contributing to an increase in artisanal fishing landings and improving the economic conditions of fishermen (Guerrero et al., 2021). As long as fishermen make sustainable use and management of the resources, the EZAF can reduce their vulnerability to the indirect impacts of climate change on fishery resources.

Climate change affects the conditions of the oceans (temperature, salinity, currents, pH, nutrients) and influences distribution, abundance, and primary productivity, with consequences for fishery production. The tropics and subtropics are the most affected, especially due to the increase in temperature, leading to marine species moving to areas where habitat conditions favor their development (FAO, 2018). In response to the warming of the ocean surface, changes are already occurring in the horizontal and vertical distribution of coastal fish (Hobday et al., 2015). Selvaraj et al. (2022b) projected future changes in the distribution of medium pelagic fish in the Colombian Pacific under climate change scenarios, finding that Euthynnus lineatus and Scomberomorus sierra will move away from the coast and spread to greater depths. These changes will negatively affect artisanal fishing, as catches of these species are currently made in coastal areas (Selvaraj et al., 2022b).

To model an MPA, decision support programs can be used, which allow projecting areas that group representative components of biodiversity based on objective criteria (Pasnin et al., 2016). However, it is necessary for the generated models to be validated with the fishing community (Hinchley et al., 2007; Ardron et al., 2010), in order to create an area that contains both the perspective required to maintain ecosystem and productivity conditions at a low cost and the vision of the territory of the people involved in the economic activity (le Pape et al., 2014; Ruiz Frau et al., 2015; le Cornu et al., 2018).

It is believed that marine areas oriented towards the sustainable management of fishery resources are valuable options for adhering to the principles and guidelines of the Code of Conduct for Responsible Fishing (FAO, 2001). Consequently, the implementation of EZAF not only enhances the economic activity of artisanal fishing, but also improves the economic conditions of the communities that depend on these fishery resources (Fundación MarViva, 2022). Therefore, the objective of this study was to define an EZAF as a strategy for the sustainable use of fishery resources and for the adaptation to climate change by artisanal fishermen in the southern Colombian Pacific, thus reducing their vulnerability.

STUDY AREA

The region under study corresponds to a marine coastal area in the southern Pacific of Colombia, in the department of Nariño. It includes the municipalities of San Andrés de Tumaco, Francisco Pizarro, Mosquera, Olaya Herrera, La Tola, El Charco, and Santa Barbara (Figure 1). Within the study area, there are three areas that belong to the Colombian National System of Protected Areas (SINAP): Gorgona Natural National Park, Sanquianga Natural National Park, and the Cabo Manglares, Bajo Mira y Frontera National District of Integrated Management). This zone includes mangroves, estuaries, esteros, and beaches that provide ecosystem services, such as provisioning (i.e., food and raw materials) and coastal erosion regulation (Delgado et al., 2008).

Figure 1 Study area and location of the national protected areas (PNN: Parque Nacional Natural; DNMI: National Integral Management District). 

The region’s economy is primarily based on the extraction and exploitation of natural resources through forestry, fishing, and livestock (Gobernación de Nariño, 2012). Fishing is one of the main economic activities, as it generates direct employment and provides food security to approximately 13000 families of artisanal fishers (Herrera et al., 2019). In the coastal municipalities of the department of Nariño (Tumaco, Francisco Pizarro, Mosquera, Olaya Herrera, La Tola, El Charco, and Santa Bárbara), more than 98 % of the population have their basic needs unmet, and 70 % of the population in these municipalities live in conditions of poverty (Departamento Administrativo Nacional de Estadística, 2018; López et al., 2008).

The area for identifying the EZAF included 50 km of ocean from the coastline, corresponding to the coastal area of activity for artisanal fishers (Inshore Fishing Area, or IFA) (Chuenpagdee et al., 2006). Additionally, 5.4 km of terrestrial area from the coastline were added to the include terrestrial ecosystems and land uses that could impact the performance of the EZAF. This is because the coastal terrestrial subzone, which extends from the Mean High Tide Line to a parallel line located 2 km inland (Article 2.2.4.2.1.1 of Decree 1076 of 2015), would be insufficient to evaluate critical areas, such as the rural zones where the coverage of original ecosystems is less than 50 % - in some cases, it is even less than 20 % (Garay, 2006; IDEAM et al., 2017). According to the Planning and Integral Management Plan of the UAC-LIAS, this area could exhibit monocultures or illicit crops, which have negative environmental impacts on marine-coastal ecosystems (Garay, 2006). Moreover, there are transitional forests, which are crucial for the health of the mangrove ecosystem, such as the Natal, Sajal, and Naidizal forests, given their ability to retain sediments and pollutants (López et al., 2008).

MATERIALS AND METHODS

A marine protected area was modeled using the Marxan software (Ball et al., 2009), a decision-making tool widely used and accepted by the international community due to its potential to analyze complex datasets and its flexibility in developing scenarios and alternatives (Ball et al., 2009). Additionally, it is a free software application that can be used by decision-makers in low-income countries (Janßen et al., 2019). Although the program is intended for modeling protected areas with a conservation focus, it can also be used for modeling areas with a sustainable use focus (Henriques et al., 2017; Baker et al., 2019; Janßen et al., 2019). All the datasets used in the modeling and their sources are presented in Table 1.

Table 1 Data used for modeling in Marxan 

The study area was divided into a grid of 2 x 2 km2 Planning Units (PU) using the create Fishnet tool in ArcGIS 10.6 (Ardron et al., 2010; Giménez et al., 2021), obtaining a total of 3821 PU.

CONSERVATION OBJECTS (COS)

The marine ecosystems considered were cliffs, shallows, estuaries, mangroves, and beaches. Other objects of conservation were turtle nesting beaches and sedimentary facies. The continental ecosystems that did not show anthropic alterations were classified as objects of conservation, and those that did were regarded as threats in the cost layer.

Information on artisanal fishing grounds was obtained in 1,852 x 1,852 km2 (nm2) grids, representing the number of fishing activities per unit area for each type of fishing gear (handline and longline). It was divided into two classes, using the natural breaks or Jenks classification of ArcGIS in order to group similar values and maximize the differences between classes (Liu et al., 2019). The layers obtained were classified as having high and low frequency. Industrial fishing grounds and their navigation routes were used as threats in the cost layer given the overexploitation of some commercial species in the Pacific (Saavedra-Díaz et al., 2015; Arroyo et al., 2016; Jiménez and Saavedra, 2019). Artisanal fishing grounds using changa were also included in the cost layer, as this type of fishing gear is not regulated and has a high impact on the target fishing species.

25 species of bony fish, 5 of mollusks, 7 of crustaceans, 25 of rays and sharks, 2 of turtles, 1 of whale (humpback whale), 3 of dolphins, and 1 of sperm whale were selected; these marine species are targets of artisanal fishing (fish, mollusks, and crustaceans) or allow for alternative activities such as ecotourism (whales, rays, sharks, turtles, and dolphins). Some species were grouped by functional groups (pelagic, benthopelagic, demersal, reef-associated, shrimps and crabs, and lobsters), and others by groups of ecosystem and touristic interest (sharks, mollusks, rays, whales, dolphins, sperm whales, and turtles) (Zeller and Pauly, 2015). These objects of conservation were classified as having high and low frequency. Figure 2 shows the distribution of the different data used in the modeling.

Figure 2 Conservation objects distribution and threats in the study area. A: ecosystems; B: bottom types; C: occurrence distribution; D: fishing grounds and routes; E: continental ecosystems; F: distribution of fishing gear use. 

COST LAYER

The cost layer was composed of the geographic components that alter the cost-benefit relationship of the study area and can cause alterations to ecosystem services or the income from fishing activity (Alonso et al., 2008; Gutiérrez et al., 2008; Ardron et al., 2010; Baker et al., 2019; Li et al., 2020). The following threats were spatially located: population centers; ports; industrial fishing grounds and routes for tuna, deep-water shrimp, shallow-water shrimp, small pelagics, and whitefish; artisanal fishing grounds using changas; terrestrial ecosystems; non-differentiated, intervened rural areas (< 20 % of remaining original ecosystems), non-differentiated, intervened rural areas (20 to 50 % of the remaining original ecosystems); and agroecosystems. The threat layers were overlaid on the planning units layer (PU) and assigned a value of 1 or 0 if the threat was or was not present in the PU. The cost of each PU was the product between the number of threats present in the same unit and the area of the PU (Alonso et al., 2008; Dalmau, 2020), which was obtained using the following equation:

RESULTS

COST

The maximum value associated with the sum of threats per PU was 4. The area value for each PU was 400 ha. The product between the sum of threats and the area of each PU yielded the following four classes: 1600, 1200, 800, and 400 (Figure 3).

Figure 3 Cost associated with each planning unit in the study area to model the Exclusive Zone for Artisanal Fishing in the Nariño Pacific. 

SPATIAL ANALYSIS

The best solution for scenario 1 was 1,024 PUs, equivalent to an area of 4,096 km2 (26.8 % of the study area), out of which 82.1 % corresponded to protected areas (Figure 4A). This solution grouped the PUs with the highest frequencies within the protected areas, some in Tumaco Bay and north of the study area (Figure 4D), while also meeting the inclusion goal for all COs.

Figure 4 Scenarios that represent the best solutions considering the selected PUs (A-C) and frequencies (D-E). In A-C, green indicates ‘optimal’ PUs for the EZAF. In D-F, dark blue areas represent those that are the most useful for generating efficient solutions. Scenario 1: A and D; Scenario 2: B and E; Scenario 3: C and F. 

The total number of PUs in the best solution for scenario 2 was 393 (1,572 km2), corresponding to 10.3 % of the study area (Figure 4B). This solution included several groups of high-frequency PUs along the coast, such as those located at the center of the study area, where artisanal and subsistence fishing is carried out (Figure 4E). In this scenario, the inclusion of 45 COs was achieved. The best solution met the inclusion goals for artisanal fishing grounds and areas of occurrence for functional groups of interest.

In scenario 3, the best solution corresponded to 428 PUs, equivalent to an area of 1,712 km2 (Figure 4C), meeting the inclusion goals for 49 COs. The best solution showed an area to the northwest of the Sanquianga NNP, which contains a greater grouping of functional groups and artisanal fishing activity. However, the PU selection frequency was lower in comparison with the previous two scenarios (Figure 4F). This scenario considers 54 % of the current MPAs.

As for the result of the participatory cartography workshop, the fishermen indicated that the area selected for the EZAF is near the coast, located between Cabo Manglares and the San Juan River Mouth (Figure 5). They selected a total of 867 PUs (3,468 km2).

Figure 5 Area proposed by the artisanal fishermen. Planning units selected more than 50 % of the time (left) - PU selection frequencies (left). 

Upon overlaying the scenarios modeled in Marxan with that proposed by the fishermen, scenario 5 was obtained (Figure 6), comprising a total of 502 PUs (2,008 km2) located on the coast of Tumaco and Francisco Pizarro. This scenario included 32 of the 52 COs (Table 2). Among the COs that met the inclusion goal, ecosystems supporting fishing activity (mangroves, estuaries) and handline fishing grounds (a frequently used fishing gear) were highlighted, while also achieving the inclusion of areas where pelagic and demersal species, mollusks, shrimps, and jaibas are distributed (Table 2).

Figure 6 Potential Exclusive Zone for Artisanal Fishing created in a participatory manner with artisanal fishermen in the area. 

Table 2 Conservation Objects (COs), including the area of each one and an evaluation of the fulfillment of inclusion goals in the EZAF created in a participatory manner with artisanal fishermen. TDF: Tall Dense Forest; MDF: Medium Dense Forest; LOF Low Open Forest; NIMD: National Integrated Management District. 

The results of the survey showed that 90 % of the fishermen would be willing to participate in the implementation of an Exclusive Zone for Artisanal Fishing (EZAF) in their territory. 80 % of the surveyed population agreed or strongly agreed that the experience gained by fishermen in the northern Pacific in creating an artisanal fishing zone would be useful for their region. Moreover, the majority of fishermen agreed or strongly agreed that the EZAF would help them ensure the abundance of fish for the development of artisanal fishing (80 %), that it would contribute to an increase in catches (83 %), that it would reduce operating costs (80 %), that it would reduce the pressure of industrial fishing on the species (76 %), that it would reduce the risk of species overexploitation (74 %), and that it would reduce their vulnerability to climate change (77 %). Finally, the fishermen considered that the main threat affecting artisanal fishing is water pollution (67 %), followed by industrial fishing (47 %), overfishing (43 %), and extreme climatic phenomena (33 %).

The similarity in the classification of the combined solution of scenarios 1 and 2, as evaluated with Cohen’s kappa coefficients, was 0.04. The value for scenarios 1 and 3 was 0.19, and, for scenarios 2 and 3, it was 0.46 (Table 3). When comparing the overlap between scenarios, the greatest similarities were observed in class 0 (76.6 %, 74.0 %, and 98.3 %, respectively), that is, in the PUs that were not frequently selected by the program regarding the three scenarios. In the following categories, the percentage of overlap decreased as the frequency of selection increased, indicating that the number of PUs classified in the classes with the highest frequency of selection differed between scenarios.

Table 3 Similarity between the three Marxan-modeled scenarios, using the kappa coefficient and upon the basis of frequency classes. 

When the best solution among the four scenarios was compared, it was found that the coefficient values were negative between scenarios 4 and 1 (-0.1) and 4 and 3 (-0.1). Between scenarios 4 and 2, the value was positive (0.4), indicating a good degree of similarity (Table 4) (Ruiz-Frau et al., 2015; Zhang and Vincent, 2019). The comparison between scenarios 4 and 2 showed the highest similarity values and overlap percentages for both the selected and non-selected areas.

Table 4 Similarity between the three Marxan-modeled scenarios and that of the fishermen, using the kappa coefficient and upon the basis of frequency classes. 

DISCUSSION

The results obtained from the Marxan modeling indicate that the current MPAs contribute to the maintenance of ecosystems and species occurrence areas within the study area. This is because the MPAs preserve elements such as mangroves, estuaries, shallows, esteros, beaches, breeding zones, and nurseries for pelagic species, among others. Although these elements are not within an EZAF, they provide ecosystem services that contribute to the abundance and biodiversity of species in fishing areas. The scenarios have benefits since they are located in areas close to the territory’s currently established MPAs, allowing for connectivity between these areas and the EZAF. Additionally, the communities of marine-coastal species that inhabit the current MPAs could migrate to new areas of the EZAF, yielding fish of large sizes. These fish, in addition to generating potential for capture, provide fry, juveniles, and adults to begin the recovery of the ecosystems within the zone (le Cornu et al., 2018; le Pape et al., 2014; Matera, 2016). Scenario 3 shows that MPAs contribute more significantly to the conservation of marine ecosystems but are not precisely areas with artisanal fishing grounds or occurrence zones for target species, as the software only used a fraction of them.

When comparing the scenarios obtained in Marxan, it was identified that scenario 2 establishes a larger area in the external zones to the MPAs, offering the opportunity to more efficiently distribute aggregation and fishing efforts. Additionally, it considers the contribution of current MPAs in terms of ecosystem conservation and the inclusion of zones that enable the development of species life cycles, such as nursery areas, where species spend the early stages of their biological cycle and later contribute to the underlying fisheries through overflow effects (le Pape et al., 2014; le Cornu et al., 2018; Baker et al., 2019; Nickols et al., 2019).

Comparisons between scenarios 1, 2, and 3 indicate that, despite exhibiting ‘low similarities’ in the first two cases (kappa < 0.4) and just ‘good’ similarities in the comparison of scenarios 2 and 3 (kappa greater than or equal to 0.4), each solution contains elements representative of the territory, such as ecosystems, artisanal fishing grounds, and species occurrence zones, which are necessary for the proper development of artisanal fishing (Pasnin et al., 2016; Zhang and Vincent, 2019). The three scenarios showed two common areas, one in Tumaco Bay and another near the Pasacaballos bank. These places harbor several COs from the study area, indicating that they are important given their contribution in meeting the inclusion goals of each CO in the EZAF (Ardron et al., 2010).

Scenario 4 shows that artisanal fishermen are aware of the limitations for their catches, therefore selecting zones adjacent to the coastline. Additionally, the location of the selected area may also be due to other factors such as the knowledge of and the frequency of use in the area near the coast (Bell et al., 2015; Hanich et al., 2018; le Cornu et al., 2018). Fishermen identified the EZAF as a strategy that would help to reduce their vulnerability to various threats such as overexploitation, industrial fishing, pollution, and, ultimately, climate change. This acceptance corroborates that the implementation of marine zones for artisanal fishing as an alternative for the sustainable use of resources and threat control generates conditions for ecosystem-based adaptation, thus validating the EZAF as an adequate strategy for the population in the study area (le Pape et al., 2014; le Cornu et al., 2018).

The similarity between scenarios 2 and 4 shows that the population and the software coincide in the location of the EZAF, as the fishermen choose places where they perform fishing activities while reducing the pressure from other incompatible uses such as industrial fishing. The software, in turn, seeks a strategic place based on cost benefit factors such as the distance between PUs, the cost associated with each PU, and the number of COs included, among others (Baker et al., 2019; Ban et al., 2009). This is why community participation is important in identifying optimal zones for artisanal fishing, as they know the territory and can identify the most suitable areas based on their experience and traditional knowledge. Likewise, this process aids in the appropriation of the results by the communities. Solution 2 excluded MPAs and was the most similar to scenario 4. This may be due to the fact that fishermen select areas that are not under a protection scheme and identify zones where they can freely carry out fishing activities.

By combining the proposals of the software and the fishermen to obtain the final result, a solution was obtained which includes an area sufficient for fishermen to carry out their activity without affecting the location of their fishing grounds, as well as strategic ecosystems and the distribution zones of species of fishing interest, which is reflected in the COs included in scenario 5 (Ruiz-Frau et al., 2015). This scenario includes zones where ecotourism activities can be carried out, such as whale or bird watching, thus constituting additional sources of income. It includes various fishery resources, offering possible alternatives in terms of diversifying the target species for capture during closed seasons or in the face of possible alterations in species distribution due to climate change. This scenario also provides adequate habitats for ecosystems to improve their condition and manage to provide the population with food and income (le Cornu et al., 2018). Furthermore, it includes ecosystems such as mangrove forests, which control coastal erosion, enable the development of species in their juvenile stage, capture greenhouse gas emissions, and provide fishing species such as jaibas, pianguas, and others that inhabit these zones (Sierra and Cantera, 2015).

The results obtained in the survey indicate that the EZAF is an ecosystem-based adaptation strategy, which is accepted by the community and perceived as an alternative to ensure the sustainability of fishing activities over time (le Cornu et al., 2018). Moreover, by having less pressure on the ecosystems due to the exclusion of industrial activities and other threats, they can maintain a high productivity, as long as effective management measures for sustainable artisanal fishing are implemented (efforts, gear, sizes, temporal and spatial closures) (Jamero et al., 2019). It can be highlighted that fishermen identify the negative effect of climate variability (ENSO) on fishing. In addition, a greater proportion of the respondents identify pollution, industrial fishing, and overfishing as negative factors which should be appropriately managed in order to reduce the vulnerability of the population.

Given that climate change can cause alterations in the distribution and abundance of species of commercial and cultural interest in the Pacific, choosing an area with fixed boundaries and not considering the distribution of target species or future alternatives might imply difficulties in meeting food and economic needs. Moreover, it can affect fishermen if they are conditioned to carry out fishing activities in a limited area. To make changes in the location and the boundaries of the zone according to the conditions of the resource, it would be necessary to study the distribution and abundance of species under the effects of climate change, the behavior of ecosystems, and the trends of fishing activities (le Cornu et al., 2018). It should be clarified that defining an EZAF does not mean that the community must fish exclusively in this zone, but rather that artisanal fishermen are the only ones who can extract in this area, and that rules are established against other economic activities and their possible effect on the development of marine communities. This is why, in the case of the migration of species, fishermen can carry out their activities in areas outside the EZAF. In addition, there is the possibility that other commercially interesting species, which currently do not have distribution in the territory, may arrive (le Pape et al., 2014).

The planners of such areas can consider different scenarios based on the inclusion or exclusion of MPAs as contributing to the issue of COs in the territory, in order to assess the contribution of EZAF to the conservation of representative elements for the connectivity of ecosystems and/or the contribution of MPAs to the inclusion of important ecosystems and to the flow of resources to areas where artisanal fishing is carried out (Cuervo et al., 2018). The results of this work provide a technical basis for evaluating the implementation of an EZAF in the territory by the competent authorities. Scientific and technical knowledge are important aspects on which decisions for the sustainable use of marine resources in coastal areas should be based (López et al., 2008). Furthermore, one of the problems identified in the Planning and Integral Management Plan for the Coastal Environmental Unit of the Southern Plains (where the EZAF is located) is environmental zoning. Here, an area is proposed for the sustainable use of the coastal zone’s marine resources, considering the characteristics of the socio-ecosystem to support sustainable use in the long term (López et al., 2008). At the same time, it can be part of a solution to the vulnerability of the population and the marine-coastal ecosystems to natural threats. It is also important to consider that an EZAF can be established in the territory if and only if the administration, which is led by the AUNAP in co-management with the communities, fulfills the duty to regulate and perform prevention, surveillance, and control activities with regard to industrial fishing and unregulated or harmful artisanal fishing practices such as changas, which is used in marine-coastal areas and affects the proper development of target fishing species (Satizábal, 2018; Guerrero et al., 2021; Jiménez and Saavedra, 2019).

It is recommended that the establishment process be carried out hand in hand with the communities, economic sectors, and administrators, in order to achieve a solid process supported by participatory work. This allows for appropriation and control by the users of the EZAF and avoids impositions that conflict with the cultural values and traditional knowledge of the populations (López et al., 2008; Ruiz-Frau et al., 2015; Saavedra-Díaz et al., 2015). To this effect, the participatory process carried out for establishing the EZAF in the northern Pacific should be taken as an example. This process involved different actors such as fishing authorities, National Natural Parks, Regional Autonomous Corporations, and community councils. Here, co-management has yielded better results than in other areas whose implementation process was different. Moreover, it has allowed improving the recovery of fishery resources, to the point that the inhabitants claim that there has been a 100 % recovery (Jiménez and Saavedra, 2019; Guerrero et al., 2021).

CONCLUSIONS

The three scenarios considered (Pus that include MPAs, Pus that exclude MPAs, and the inclusion of any PU) to identify a potential EZAF in the Nariño Pacific included a variety of conservation objects upon the basis of ecosystems with the potential to maintain diverse fishery resources that favor the income of fishermen. The potential EZAF, located in Tumaco Bay and selected by Marxan, corresponded to the second scenario; it included the largest area additional to the MPAs and was the one with the greatest similarity to the scenario chosen by the fishermen, since they did not include areas that had any protection mechanism.

The defined EZAF connects the protected marine areas of the Cabo Manglares, Bajo Mira y Frontera National Integrated Management District, the Sanquianga NNP, and the Gorgona NNP, forming a biological corridor to maintain biodiversity.

The criteria used in this study for the selection of the EZAF are complementary and support the fact that the local knowledge of fishermen and technical knowledge are fundamental in any process carried out on a specific area (such as an EZAF). Incorporating artisanal fishermen and their knowledge from the beginning empowers and strengthens them; the agreements reached between them, and with the fishing and environmental authorities, lead to the sustainable use of resources, and to the EZAF being maintained over time, which makes it a strategy for adaptation to climate change.

We recommend evaluating the spatial and temporal dimensions, given the effect of climate change on species distribution.